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Data Science for Marketing Analytics

You're reading from   Data Science for Marketing Analytics A practical guide to forming a killer marketing strategy through data analysis with Python

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781800560475
Length 636 pages
Edition 2nd Edition
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Tools
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Authors (3):
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Vishwesh Ravi Shrimali Vishwesh Ravi Shrimali
Author Profile Icon Vishwesh Ravi Shrimali
Vishwesh Ravi Shrimali
Mirza Rahim Baig Mirza Rahim Baig
Author Profile Icon Mirza Rahim Baig
Mirza Rahim Baig
Gururajan Govindan Gururajan Govindan
Author Profile Icon Gururajan Govindan
Gururajan Govindan
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Toc

Table of Contents (11) Chapters Close

Preface
1. Data Preparation and Cleaning 2. Data Exploration and Visualization FREE CHAPTER 3. Unsupervised Learning and Customer Segmentation 4. Evaluating and Choosing the Best Segmentation Approach 5. Predicting Customer Revenue Using Linear Regression 6. More Tools and Techniques for Evaluating Regression Models 7. Supervised Learning: Predicting Customer Churn 8. Fine-Tuning Classification Algorithms 9. Multiclass Classification Algorithms Appendix

Class-Imbalanced Data

Consider the scenario we discussed at the beginning of the chapter about the online shopping company. Imagine that out of the four shortlisted sellers, one is a very well-known company. In such a situation, there is a high chance of this company getting most of the orders as compared to the rest of the three sellers. If the online shopping company decided to divert all the customers to this seller, for a large number of customers, it would actually end up matching their preference. This is a classic scenario of class imbalance since one class is dominating the rest of the classes in terms of data points. Class imbalance is also seen in fraud detection, anti-money laundering, spam detection, cancer detection, and many other situations.

Before you go into the details about how to deal with class imbalance, let's first see how it can pose a big problem in a marketing analyst's work in the following exercise.

Exercise 9.03: Performing Classification...

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